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Personalized Search and Visualization Techniques for Enhanced News Retrieval

This presentation by Jae-wook Ahn at the PAWS meeting on March 23, 2007, explores advanced personalized search and visualization methods for news articles. Highlighting the baseline vector space model, TF-IDF weighting, and cosine similarity, it delves into techniques for query expansion using user-identified terms. A significant focus is on the VIBE visualization tool, which separates points of interest to enhance user interaction. Attendees will learn about the roles of query terms and the impact of automatic query expansion in improving search personalization and user experience.

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Personalized Search and Visualization Techniques for Enhanced News Retrieval

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Presentation Transcript

  1. Personalized Search and Visualization for YourNews Jae-wook Ahn PAWS Meeting 03/23/2007

  2. Personalized Search • Baseline • Standard vector spaced model based search • TF-IDF weighting • Krovetz stemming • Cosine similarity • Personalization • Query expansion by N UM terms • N = 5

  3. Personalized visualization • VIBE visualization • POI – query terms • Documents – Search results (news articles) • Personalization • POI separation • User query terms • UM terms • POI presentation • Dual positioning of POI’s (cf. circular) • Color coding

  4. Personalized visualization (cont’d) • Users can see, • Roles of each query term – baseline VIBE • How automatic query expansion (or personalization) works • Roles of user query terms – baseline search • Roles of system UM terms - personalized search

  5. Demonstration • http://ir.exp.sis.pitt.edu/gale/news

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